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Dear All,

 

I hope this message finds you well. We are thrilled to extend opportunities to join our team at the Johns Hopkins University in developing a three-dimensional atlas of the human body, BodyMaps. We are actively seeking several skilled and passionate students to make substantial contributions to this program.

 

About the BodyMaps Program

 

BodyMaps is a rigorously mentored research program at the convergence of Artificial Intelligence (AI) and Medicine, hosted at the Computational Cognition, Vision, and Learning (CCVL) lab. It welcomes students, researchers, clinicians, and developers around the world. Over 9 to 12 months, candidates will lead high-impact research, receive training and working in small interdisciplinary teams.

BodyMaps AI Bootcamp

We can host visiting students from outside Hopkins. There are multiple training positions open for undergraduates, graduate students, and post-doctoral scholars:

Rolling applications, reviewed at the end of every month.

Mentors

 

Prof. Zongwei Zhou is the director of the BodyMaps program, and directly mentors each project. The program is overseen by highly qualified mentors who are experts in their respective fields. Each project is assigned one or more mentors, ensuring access to top-tier expertise and direct mentorship.

 

  • Zongwei Zhou, PhD | Assistant Research Professor | Johns Hopkins University

  • Alan Yuille, PhD | Bloomberg Distinguished Professor | Johns Hopkins University

  • Pedro R. A. S. Bassi, PhD | Postdoctoral Fellow | Johns Hopkins University

  • Heng Li, PhD | Associate Professor | Johns Hopkins Medicine

  • Kai Ding, PhD | Associate Professor | Johns Hopkins Medicine

  • Yang Yang, PhD | Associate Professor | University of California, San Francisco

  • Kang Wang, MD, PhD | Assistant Professor | University of California, San Francisco

  • Arkadiusz Sitek, PhD | Associate Professor | Harvard University

  • Yucheng Tang, PhD | Senior Research Scientist | Nvidia

  • Szymon Płotka, PhD | Assistant Professor | Jagiellonian University

 

JHU students can get research units with Prof. Zongwei Zhou.

The position can be either in-person or remote, though in-person participation is encouraged.

BodyMaps Demonstration Award

​The BodyMaps Demonstration Award provides multiple one-year awards of up to $100,000 to support projects with strong potential to develop AI algorithms for early cancer detection from CT scans of the abdomen, pelvis, and chest. The program emphasizes multi-cancer early detection and prioritizes innovative approaches that demonstrate the potential to significantly outperform expert radiologist performance in both sensitivity and specificity.

All letter of intents should be submitted as PDFs here.

Thank you.

Previous Projects

November 24, 2025

CCVL researchers to present 18 abstracts at RSNA 2025

The Annual Meeting of the Radiological Society of North America is the premier, global radiology conference where the power of imaging, education, and collaboration come to life.

> View Story

Contributed by many previous intern students

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February 19, 2025

AbdomenAtlas: an AI-based approach for early cancer diagnosis

AbdomenAtlas is an extensive dataset of 3D reconstructed and annotated abdominal CT scans that can be used to train AI technology on identifying cancer. 

> View Story

Wenxuan Li, Master's student at Johns Hopkins University, 2023-2024

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February 17, 2025

A Touchstone of Medical Artificial Intelligence

Johns Hopkins researchers release a new standard for evaluating medical AI models to promote fairness and reduce bias.

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Pedro R. A. S. Bassi, PhD student at University of Bologna, 2024-2025

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August 22, 2024

Forget-Me-Not: Selective Memory Can Help AI Remember More, Not Less

Inspired by human learning patterns, Johns Hopkins computer scientists have developed a new technique to train AI models on massive amounts of medical data without forgetting what they’ve already learned.

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Yu-Cheng Chou, Master's student at Wuhan University, 2022-2023

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May 30, 2024

Johns Hopkins Researchers Create Artificial Tumors to Help AI Detect Early-Stage Cancer

The Hopkins-led team demonstrated that an AI model trained solely on synthetic tumor data works as well as models trained on real tumors.

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Qixin Hu, Master's student at Huazhong University of Science and Technology, 2022-2023

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February 9, 2024

AI and Radiologists Unite to Map the Abdomen

Hopkins researchers have leveraged the synergy between medical professionals and artificial intelligence algorithms to create the largest annotated multi-organ dataset to date.

> View Story

Chongyu Qu, Master's student at Johns Hopkins University, 2023-2024

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